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* agents - phase 1 (#30) * chore: copy assistant files * feat: frontend and data-provider * feat: backend get endpoint test * fix(MessageEndpointIcon): switched to AgentName and AgentAvatar * fix: small fixes * fix: agent endpoint config * fix: show Agent Builder * chore: install agentus * chore: initial scaffolding for agents * fix: updated Assistant logic to Agent Logic for some Agent components * WIP first pass, demo of agent package * WIP: initial backend infra for agents * fix: agent list error * wip: agents routing * chore: Refactor useSSE hook to handle different data events * wip: correctly emit events * chore: Update @librechat/agentus npm dependency to version 1.0.9 * remove comment * first pass: streaming agent text * chore: Remove @librechat/agentus root-level workspace npm dependency * feat: Agent Schema and Model * fix: content handling fixes * fix: content message save * WIP: new content data * fix: run step issue with tool calls * chore: Update @librechat/agentus npm dependency to version 1.1.5 * feat: update controller and agent routes * wip: initial backend tool and tool error handling support * wip: tool chunks * chore: Update @librechat/agentus npm dependency to version 1.1.7 * chore: update tool_call typing, add test conditions and logs * fix: create agent * fix: create agent * first pass: render completed content parts * fix: remove logging, fix step handler typing * chore: Update @librechat/agentus npm dependency to version 1.1.9 * refactor: cleanup maps on unmount * chore: Update BaseClient.js to safely count tokens for string, number, and boolean values * fix: support subsequent messages with tool_calls * chore: export order * fix: select agent * fix: tool call types and handling * chore: switch to anthropic for testing * fix: AgentSelect * refactor: experimental: OpenAIClient to use array for intermediateReply * fix(useSSE): revert old condition for streaming legacy client tokens * fix: lint * revert `agent_id` to `id` * chore: update localization keys for agent-related components * feat: zod schema handling for actions * refactor(actions): if no params, no zodSchema * chore: Update @librechat/agentus npm dependency to version 1.2.1 * feat: first pass, actions * refactor: empty schema for actions without params * feat: Update createRun function to accept additional options * fix: message payload formatting; feat: add more client options * fix: ToolCall component rendering when action has no args but has output * refactor(ToolCall): allow non-stringy args * WIP: first pass, correctly formatted tool_calls between providers * refactor: Remove duplicate import of 'roles' module * refactor: Exclude 'vite.config.ts' from TypeScript compilation * refactor: fix agent related types > - no need to use endpoint/model fields for identifying agent metadata > - add `provider` distinction for agent-configured 'endpoint' - no need for agent-endpoint map - reduce complexity of tools as functions into tools as string[] - fix types related to above changes - reduce unnecessary variables for queries/mutations and corresponding react-query keys * refactor: Add tools and tool_kwargs fields to agent schema * refactor: Remove unused code and update dependencies * refactor: Update updateAgentHandler to use req.body directly * refactor: Update AgentSelect component to use localized hooks * refactor: Update agent schema to include tools and provider fields * refactor(AgentPanel): add scrollbar gutter, add provider field to form, fix agent schema required values * refactor: Update AgentSwitcher component to use selectedAgentId instead of selectedAgent * refactor: Update AgentPanel component to include alternateName import and defaultAgentFormValues * refactor(SelectDropDown): allow setting value as option while still supporting legacy usage (string values only) * refactor: SelectDropdown changes - Only necessary when the available values are objects with label/value fields and the selected value is expected to be a string. * refactor: TypeError issues and handle provider as option * feat: Add placeholder for provider selection in AgentPanel component * refactor: Update agent schema to include author and provider fields * fix: show expected 'create agent' placeholder when creating agent * chore: fix localization strings, hide capabilities form for now * chore: typing * refactor: import order and use compact agents schema for now * chore: typing * refactor: Update AgentForm type to use AgentCapabilities * fix agent form agent selection issues * feat: responsive agent selection * fix: Handle cancelled fetch in useSelectAgent hook * fix: reset agent form on accordion close/open * feat: Add agent_id to default conversation for agents endpoint * feat: agents endpoint request handling * refactor: reset conversation model on agent select * refactor: add `additional_instructions` to conversation schema, organize other fields * chore: casing * chore: types * refactor(loadAgentTools): explicitly pass agent_id, do not pass `model` to loadAgentTools for now, load action sets by agent_id * WIP: initial draft of real agent client initialization * WIP: first pass, anthropic agent requests * feat: remember last selected agent * feat: openai and azure connected * fix: prioritize agent model for runs unless an explicit override model is passed from client * feat: Agent Actions * fix: save agent id to convo * feat: model panel (#29) * feat: model panel * bring back comments * fix: method still null * fix: AgentPanel FormContext * feat: add more parameters * fix: style issues; refactor: Agent Controller * fix: cherry-pick * fix: Update AgentAvatar component to use AssistantIcon instead of BrainCircuit * feat: OGDialog for delete agent; feat(assistant): update Agent types, introduced `model_parameters` * feat: icon and general `model_parameters` update * feat: use react-hook-form better * fix: agent builder form reset issue when switching panels * refactor: modularize agent builder form --------- Co-authored-by: Danny Avila <danny@librechat.ai> * fix: AgentPanel and ModelPanel type issues and use `useFormContext` and `watch` instead of `methods` directly and `useWatch`. * fix: tool call issues due to invalid input (anthropic) of empty string * fix: handle empty text in Part component --------- Co-authored-by: Marco Beretta <81851188+berry-13@users.noreply.github.com> * refactor: remove form ModelPanel and fixed nested ternary expressions in AgentConfig * fix: Model Parameters not saved correctly * refactor: remove console log * feat: avatar upload and get for Agents (#36) Co-authored-by: Marco Beretta <81851188+berry-13@users.noreply.github.com> * chore: update to public package * fix: typing, optional chaining * fix: cursor not showing for content parts * chore: conditionally enable agents * ci: fix azure test * ci: fix frontend tests, fix eslint api * refactor: Remove unused errorContentPart variable * continue of the agent message PR (#40) * last fixes * fix: agentMap * pr merge test (#41) * fix: model icon not fetching correctly * remove console logs * feat: agent name * refactor: pass documentsMap as a prop to allow re-render of assistant form * refactor: pass documentsMap as a prop to allow re-render of assistant form * chore: Bump version to 0.7.419 * fix: TypeError: Cannot read properties of undefined (reading 'id') * refactor: update AgentSwitcher component to use ControlCombobox instead of Combobox --------- Co-authored-by: Marco Beretta <81851188+berry-13@users.noreply.github.com>
202 lines
7.4 KiB
JavaScript
202 lines
7.4 KiB
JavaScript
const { ToolMessage } = require('@langchain/core/messages');
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const { EModelEndpoint, ContentTypes } = require('librechat-data-provider');
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const { HumanMessage, AIMessage, SystemMessage } = require('langchain/schema');
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/**
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* Formats a message to OpenAI Vision API payload format.
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*
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* @param {Object} params - The parameters for formatting.
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* @param {Object} params.message - The message object to format.
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* @param {string} [params.message.role] - The role of the message sender (must be 'user').
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* @param {string} [params.message.content] - The text content of the message.
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* @param {EModelEndpoint} [params.endpoint] - Identifier for specific endpoint handling
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* @param {Array<string>} [params.image_urls] - The image_urls to attach to the message.
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* @returns {(Object)} - The formatted message.
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*/
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const formatVisionMessage = ({ message, image_urls, endpoint }) => {
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if (endpoint === EModelEndpoint.anthropic) {
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message.content = [...image_urls, { type: ContentTypes.TEXT, text: message.content }];
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return message;
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}
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message.content = [{ type: ContentTypes.TEXT, text: message.content }, ...image_urls];
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return message;
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};
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/**
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* Formats a message to OpenAI payload format based on the provided options.
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*
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* @param {Object} params - The parameters for formatting.
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* @param {Object} params.message - The message object to format.
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* @param {string} [params.message.role] - The role of the message sender (e.g., 'user', 'assistant').
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* @param {string} [params.message._name] - The name associated with the message.
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* @param {string} [params.message.sender] - The sender of the message.
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* @param {string} [params.message.text] - The text content of the message.
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* @param {string} [params.message.content] - The content of the message.
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* @param {Array<string>} [params.message.image_urls] - The image_urls attached to the message for Vision API.
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* @param {string} [params.userName] - The name of the user.
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* @param {string} [params.assistantName] - The name of the assistant.
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* @param {string} [params.endpoint] - Identifier for specific endpoint handling
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* @param {boolean} [params.langChain=false] - Whether to return a LangChain message object.
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* @returns {(Object|HumanMessage|AIMessage|SystemMessage)} - The formatted message.
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*/
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const formatMessage = ({ message, userName, assistantName, endpoint, langChain = false }) => {
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let { role: _role, _name, sender, text, content: _content, lc_id } = message;
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if (lc_id && lc_id[2] && !langChain) {
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const roleMapping = {
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SystemMessage: 'system',
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HumanMessage: 'user',
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AIMessage: 'assistant',
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};
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_role = roleMapping[lc_id[2]];
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}
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const role = _role ?? (sender && sender?.toLowerCase() === 'user' ? 'user' : 'assistant');
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const content = _content ?? text ?? '';
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const formattedMessage = {
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role,
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content,
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};
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const { image_urls } = message;
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if (Array.isArray(image_urls) && image_urls.length > 0 && role === 'user') {
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return formatVisionMessage({
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message: formattedMessage,
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image_urls: message.image_urls,
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endpoint,
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});
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}
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if (_name) {
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formattedMessage.name = _name;
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}
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if (userName && formattedMessage.role === 'user') {
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formattedMessage.name = userName;
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}
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if (assistantName && formattedMessage.role === 'assistant') {
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formattedMessage.name = assistantName;
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}
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if (formattedMessage.name) {
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// Conform to API regex: ^[a-zA-Z0-9_-]{1,64}$
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// https://community.openai.com/t/the-format-of-the-name-field-in-the-documentation-is-incorrect/175684/2
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formattedMessage.name = formattedMessage.name.replace(/[^a-zA-Z0-9_-]/g, '_');
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if (formattedMessage.name.length > 64) {
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formattedMessage.name = formattedMessage.name.substring(0, 64);
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}
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}
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if (!langChain) {
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return formattedMessage;
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}
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if (role === 'user') {
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return new HumanMessage(formattedMessage);
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} else if (role === 'assistant') {
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return new AIMessage(formattedMessage);
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} else {
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return new SystemMessage(formattedMessage);
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}
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};
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/**
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* Formats an array of messages for LangChain.
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*
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* @param {Array<Object>} messages - The array of messages to format.
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* @param {Object} formatOptions - The options for formatting each message.
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* @param {string} [formatOptions.userName] - The name of the user.
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* @param {string} [formatOptions.assistantName] - The name of the assistant.
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* @returns {Array<(HumanMessage|AIMessage|SystemMessage)>} - The array of formatted LangChain messages.
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*/
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const formatLangChainMessages = (messages, formatOptions) =>
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messages.map((msg) => formatMessage({ ...formatOptions, message: msg, langChain: true }));
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/**
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* Formats a LangChain message object by merging properties from `lc_kwargs` or `kwargs` and `additional_kwargs`.
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*
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* @param {Object} message - The message object to format.
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* @param {Object} [message.lc_kwargs] - Contains properties to be merged. Either this or `message.kwargs` should be provided.
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* @param {Object} [message.kwargs] - Contains properties to be merged. Either this or `message.lc_kwargs` should be provided.
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* @param {Object} [message.kwargs.additional_kwargs] - Additional properties to be merged.
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*
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* @returns {Object} The formatted LangChain message.
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*/
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const formatFromLangChain = (message) => {
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const { additional_kwargs, ...message_kwargs } = message.lc_kwargs ?? message.kwargs;
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return {
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...message_kwargs,
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...additional_kwargs,
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};
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};
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/**
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* Formats an array of messages for LangChain, handling tool calls and creating ToolMessage instances.
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*
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* @param {Array<Partial<TMessage>>} payload - The array of messages to format.
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* @returns {Array<(HumanMessage|AIMessage|SystemMessage|ToolMessage)>} - The array of formatted LangChain messages, including ToolMessages for tool calls.
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*/
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const formatAgentMessages = (payload) => {
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const messages = [];
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for (const message of payload) {
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if (message.role !== 'assistant') {
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messages.push(formatMessage({ message, langChain: true }));
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continue;
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}
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let currentContent = [];
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let lastAIMessage = null;
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for (const part of message.content) {
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if (part.type === ContentTypes.TEXT && part.tool_call_ids) {
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// If there's pending content, add it as an AIMessage
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if (currentContent.length > 0) {
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messages.push(new AIMessage({ content: currentContent }));
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currentContent = [];
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}
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// Create a new AIMessage with this text and prepare for tool calls
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lastAIMessage = new AIMessage({
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content: part.text || '',
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});
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messages.push(lastAIMessage);
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} else if (part.type === ContentTypes.TOOL_CALL) {
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if (!lastAIMessage) {
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throw new Error('Invalid tool call structure: No preceding AIMessage with tool_call_ids');
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}
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// Note: `tool_calls` list is defined when constructed by `AIMessage` class, and outputs should be excluded from it
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const { output, ...tool_call } = part.tool_call;
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lastAIMessage.tool_calls.push(tool_call);
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// Add the corresponding ToolMessage
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messages.push(
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new ToolMessage({
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tool_call_id: tool_call.id,
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name: tool_call.name,
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content: output,
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}),
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);
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} else {
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currentContent.push(part);
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}
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}
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if (currentContent.length > 0) {
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messages.push(new AIMessage({ content: currentContent }));
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}
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}
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return messages;
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};
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module.exports = {
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formatMessage,
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formatFromLangChain,
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formatAgentMessages,
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formatLangChainMessages,
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};
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